Efficient cell site outage mitigation

ABSTRACT

To efficiently mitigate cell coverage disruptions caused by either unplanned equipment failures or planned outages during maintenance activities, an efficient cell site outage mitigation system is provided to calculate an optimal configuration for neighboring cell site devices before adjusting the cell site configuration settings to cover the coverage gap. The optimal configuration is determined using an offline model learner. Radio frequency propagation models and user demand and distribution models can be used to determine the offline solution. The optimal configuration setting learnt using an offline model is then implemented when an outage is determined to have occurred in the operational field.

PRIORITY CLAIM

This application is a continuation application of, and claims priorityto, U.S. patent application Ser. No. 14/088,684, entitled “EFFICIENTCELL SITE OUTAGE MITIGATION”, and filed on Nov. 25, 2013. The entiretyof the above-referenced U.S. Patent Application is hereby incorporatedherein by reference.

TECHNICAL FIELD

The subject disclosure relates to mitigating a cell site outage, and,more specifically, to determining an optimal configuration setting for acell site device before an outage occurs.

BACKGROUND

Cell tower outages can occur in operation networks either due tounplanned equipment failures or planned maintenance activities.Traditionally, the resolution strategy is to repair the networkequipment and get the service up and running. Meanwhile, the end-userscan communicate using neighboring cell towers that are up. Depending onthe radio coverage and network capacity, some users either might bedenied service due to coverage holes or might experience a degradedquality of service due to overload conditions.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is an example, non-limiting embodiment of an efficient cell siteoutage mitigation system in accordance with various aspects describedherein.

FIG. 2 is an example, non-limiting embodiment of an efficient cell siteoutage mitigation system in accordance with various aspects describedherein.

FIG. 3 is an example, non-limiting embodiment of an efficient cell siteoutage mitigation system in accordance with various aspects describedherein.

FIG. 4 is an example, non-limiting embodiment of an efficient cell siteoutage mitigation system in accordance with various aspects describedherein.

FIG. 5 is an example, non-limiting embodiment of an efficient cell siteoutage mitigation system in accordance with various aspects describedherein.

FIG. 6 is a block diagram illustrating an example, non-limitingembodiment of an efficient cell site outage mitigation system inaccordance with various aspects described herein.

FIG. 7 is a block diagram illustrating an example, non-limitingembodiment of an efficient cell site outage mitigation system inaccordance with various aspects described herein.

FIG. 8 illustrates a flow diagram of an example, non-limiting embodimentof a method for cell site outage mitigation as described herein.

FIG. 9 is a block diagram of an example, non-limiting embodiment of acomputing environment in accordance with various aspects describedherein.

FIG. 10 is a block diagram of an example, non-limiting embodiment of amobile network platform in accordance with various aspects describedherein.

DETAILED DESCRIPTION

One or more embodiments are now described with reference to thedrawings, wherein like reference numerals are used to refer to likeelements throughout. In the following description, for purposes ofexplanation, numerous specific details are set forth in order to providea thorough understanding of the various embodiments. It is evident,however, that the various embodiments can be practiced without thesespecific details (and without applying to any particular networkedenvironment or standard).

To efficiently mitigate cell coverage disruptions caused by eitherunplanned equipment failures or planned outages during maintenanceactivities, an efficient cell site outage mitigation system is providedto calculate an optimal configuration for neighboring cell site devicesbefore adjusting the cell site configuration settings to cover thecoverage gap. The optimal configuration is determined using an offlinemodel learner. Radio frequency propagation models and user demand anddistribution models can be used to determine the offline solution. Theoptimal configuration setting learnt using an offline model is thenimplemented when an outage is determined to have occurred in theoperational field. Incremental adjustments to the configuration settingscan then be performed in a real-time fashion based on performancefeedback from the field. This helps dynamically converge to the optimalsolution.

Traditionally, incremental adjustments to antenna tilt and transmissionpower are performed from the initial, pre-outage, configuration settingto mitigate cell site outages. By determining an offline optimalsolution beforehand however, faster convergence on a real world optimalsolution can be obtained. Occasionally, incrementally adjusting antennatilt and transmission power settings from the base configuration cancause the self-organizing networks to converge on local optimalsolutions while avoiding or otherwise not arriving at global optimalsolutions. Calculating a model optimal solution beforehand can avoidconverging on these local solutions.

For these considerations as well as other considerations, in one or moreembodiments, a system includes a memory to store executable instructionsand a processor, coupled to the memory, to facilitate execution of theexecutable instructions to perform operations including determining afirst simulated configuration setting for a first cell site device basedon a simulated disablement of a second cell site device, wherein thefirst simulated configuration setting enables a simulated coverage modelfor an area associated with the first cell site device and the secondcell site device. The operations also include adjusting a configurationsetting for the first cell site device to match the first simulatedconfiguration setting in response to determining that the second cellsite is disabled. The operations also include incrementally adjustingthe configuration setting according to a function that increasescoverage for the area.

In another embodiment, a method includes determining, by a devicecomprising a processor, a model configuration setting for a first basestation device based on information relating to a disabled neighboringbase station device, wherein the model configuration setting provides acoverage model for an area associated with the first base station deviceand the disabled neighboring base station device. The method alsoincludes adjusting a configuration setting for the first base stationdevice to match the model configuration setting in response todetermining that the neighboring base station device is offline.

In another embodiment, a computer readable storage device storingexecutable instructions, that in response to execution, cause a systemcomprising a processor to perform operations. That operations caninclude modeling a simulated configuration setting for a first basestation device based on an offline second base station device thatneighbors the first base station device, wherein the simulatedconfiguration setting enables a coverage model for an area associatedwith the first base station device and the offline second base stationdevice. The operations can further include adjusting a configurationsetting for the first base station device to match the simulatedconfiguration setting in response to determining that the second basestation device is offline. The operations also include, incrementallyadjusting the configuration setting to improve coverage for the area.

Turning now to FIG. 1, illustrated is an example, non-limitingembodiment of an efficient cell site outage mitigation system 100 inaccordance with various aspects described herein. System 100 can includebase station devices or cell site devices 102, 104, and 106 withcorresponding coverage areas 112, 114, and 116 respectively. Undernormal operation, coverage areas 112, 114, and 116 can overlap,providing sufficient quality of service to mobile devices in thecoverage areas. As mobile devices move from one coverage area to thenext, they can be handed over from one cell site device to the next dueto the overlapping coverage areas.

It is to be appreciated that the system 100 shown in FIG. 1 has beensimplified for ease of understanding. In the real world, many more thanthree cell site devices and coverage areas are possible and may bearranged in a non-linear manner.

It is also to be appreciated the term “cell site device” as used withreference to cell site devices 102, 104, and 106 refers to the basetransceiver station or the set of equipment that facilitates wirelesscommunications between user equipment and the network. For instance, thecell site device can include a power source/supply, modem/router toreceive communications from the network, digital signal processors,transceivers, combiners/duplexers, antennas, and etc. The cell coveragearea refers to the area within which a mobile device or user equipmentcan send and receive communications to and from the mobile network viathe cell site device. The cell coverage area sizes and shapes can varydepending on power output of the cell site device, antenna tiltconfiguration, the local terrain/topology, interference from other radiosources, weather, and etc. The cell coverage areas in FIG. 1 are shownas ovals, but it should be appreciated that this convention is forsimplicity and that in other embodiments, other configurations arepossible.

If an outage, either planned due to maintenance or unplanned due toequipment failure, occurs to any of cell site devices 102, 104, or 106,mobile devices within the affected cell coverage area 112, 114, or 116will suffer a loss of connectivity/signal unless they are in the smallportion of the cell coverage area that overlaps with the cell coveragearea of the neighboring cell site device. For example, if cell sitedevice 102 goes offline, any mobile devices or user equipment in cellcoverage area 112 will lose connectivity with the mobile network unlessthey are in the portion of cell coverage area 112 that overlaps withcell coverage area 114. Mobile devices in the overlapping section can behanded over to cell site device 104, but other mobile devices in cellcoverage area 112 will lose their connection. Similarly, if cell sitedevice 104 suffers an outage, mobile devices in cell coverage area 114will lose connectivity unless they are in the areas that overlap withcell coverage areas 112 and 116.

Traditionally, when the outage occurs, the neighboring cell site deviceswill begin to incrementally adjust their configuration settings tomitigate the outage. If cell site device 104 goes offline, cell sitedevices 102 and 106 will adjust their settings incrementally so thatcell coverage areas 112 and 116 cover as much of former cell coveragearea 114 as possible. The iterations are performed slowly andincrementally, as the dynamics of adjusting tilt configurations withpower settings requires small adjustments and then determining the bestadjustment to make based on the outcome of the previous adjustment.

In an embodiment, a theoretical optimal configuration setting can bedetermined before the outage occurs and then once the outage isdetected, the configuration setting can be adjusted to match thetheoretical optimal configuration setting. An optimal configurationsetting can be determined for all neighboring cell site devices of thecell site device suffering an outage. Therefore, in an example, if cellsite device 104 were to go offline, a model optimal solution can bedetermined for both cell site devices 102 and 106. If cell site device102 were to go offline, model solutions can be determined for both cellsite devices 104 and 106.

Even though cell site device 106 does not directly neighbor cell sitedevice 102, as cell site 104's cell coverage area 114 will be changed tocover former cell coverage area 112, cell coverage area 116 will have toadjust based on the changes to cell coverage area 114. Similarly, anycell site device that neighbors cell site device 106 may subsequentlychange as well. The system therefore calculates model optimal solutionsfor all neighbors (1^(St) order, 2^(nd) order, 3^(rd) order, and etc) ofany cell site device that may go offline.

In an embodiment, the simulated configuration setting can be determinedbefore any outage occurs, based on planned outages, or in response to anoutage occurring. In some embodiments, the simulated configurationsetting can be determined after the outage happens, and the time takento calculate can still be faster than incrementally adjusting theexisting cell site devices.

Turning now to FIG. 2, illustrated is an example, non-limitingembodiment of an efficient cell site outage mitigation system 200 inaccordance with various aspects described herein. Shown in FIG. 2 is anembodiment where cell site device 204 has gone offline, due to either aplanned or unplanned outage. Model optimal configuration settings forcell site devices 202 and 206 can be determined either before theoutage, or shortly after the outage is detected, and cell coverage areas212 and 216 reflect the coverage of cell site devices 202 and 206respectively after the configuration settings of cell site devices 202and 206 are adjusted to match the model optimal configuration settings.

In an embodiment, while cell coverage areas 212 and 216 provide morecoverage over cell sites devices 204's former coverage area than theinitial cell coverage areas of cell site devices 202 and 206 (see e.g.,cell coverage areas 112 and 116 in FIG. 1), some improvement ispossible. Accordingly, cell site devices 202 and 206 can incrementallymake improvements in real time to the simulated optimal configuration.The improvements to the configuration settings of cell site devices 202and 206 can result in real world optimal cell coverage areas 222 and 226which provide better coverage over cell site devices 204's coverage areathan coverage areas 212 and 216. By calculating the simulated optimalconfiguration settings before implementing the configuration settings onthe cell site devices 202 and 206, convergence on the optimal solutioncan be improved over incrementally adjusting configuration settings fromthe base settings.

Turning now to FIG. 3, illustrated is an example, non-limitingembodiment of an efficient cell site outage mitigation system 300 inaccordance with various aspects described herein. In an embodiment, thecell site outage mitigation system 300 can take into account userdistribution and user demand when simulating optimal configurationsettings for cell site devices.

In the embodiment shown in FIG. 3, cell site device 304 can experiencean outage or go offline, and cell site devices 302 and 306 can havetheir configuration settings (antenna tilt, transmission power, etc)adjusted to provide coverage (shown by cell coverage areas 312 and 316respectively) for the area formerly covered by cell site device 304.

While simulating the offline configuration setting model, system 300 cantake into account the current location of mobile devices 318 and 320within the area as well as user demand. For instance, the system 300 candetermine that mobile devices 318 and 320 are closer to cell site device302 than to cell site device 306, and thus the system 300 can determinethat an optimal configuration setting for cell site devices 302 and 306would be to keep cell coverage area 316 more or less the same, whileadjusting the settings of cell site device 302 to extend the cellcoverage area 312 to cover mobile devices 318 and 320.

It is to be appreciated that while the embodiment shown in FIG. 3displays three mobile devices, this is for purposes of simplicity, andthat in the real world, a large number of mobile devices are likely. Thesystem 300 can make balancing decisions about whether to adjustconfiguration settings to cover all possible mobile devices or not. Forinstance, an area can have a high density of mobile devices, and anotherarea can have a lower density of mobile devices. If the neighboring cellsite devices cannot cover all the area experiencing an outage, but mustchoose which areas to provide coverage for, the system 300 can calculatemodel configuration settings such that the cell site devices cover thearea with the higher number of mobile devices.

The system 300 can also make the determination of model configurationsettings based on demand or priority. If mobile devices 320 and 318 arebeing heavily used, or have current sessions with higher quality ofservice standards or priority levels than mobile device 322 which isoutside of cell coverage areas 312 and 316, the system 300 can calculatemodel configuration settings to provide cell coverage for the mobiledevices 318 and 320 and not for mobile device 322.

In other embodiments, system 300 can make predictive optimalconfiguration settings, or optimal configuration settings that aredifferent based on a time that an outage occurs. For instance, duringsporting events or other public events, a large number of users andmobile devices can be present at the venue for the event. If an outageto cell site device 304 servicing the area in which the venue is locatedin occurs, the system 300 can determine that it is a higher priority toprovide service to the venue than to other areas previously served bycell site device 304. Optimal configuration settings for one or both ofcell site devices 302 and 306 can be determined based on providingservice to the venue.

In other embodiments, regular patterns of mobile device locations can beidentified such as higher density of mobile devices in a specificlocation due to jobs, commutes, rush-hour traffic, shopping centers,etc. The optimal configuration settings can be calculated to take intoconsideration these distribution and demand models.

In an embodiment, system 300 can determine the location of mobiledevices 318, 320, and 322 based on network location (multilateration) orbased on reports received from the mobile devices that are GPS equipped.In other embodiments, system 300 can make predictions about thelocations of mobile devices based on known locations of shoppingcenters, residential areas, office buildings, and etc.

Turning now to FIG. 4, illustrated is an example, non-limitingembodiment of an efficient cell site outage mitigation system 400 inaccordance with various aspects described herein. System 400 can use RFpropagation models, terrain and topology, interference, and otherfactors to determine simulated optimal configuration settings in thesame way that system 300 in FIG. 3 uses user distribution and demandmodels.

In the embodiment shown in FIG. 4, the system 400 can determine modeloptimal configuration settings for cell site devices 402 and 406 basedon a potential outage of cell site 404. The model optimal configurationsettings provide for cell coverage areas 412 and 416 that at least inpart cover areas normally covered by cell site device 404.

In an embodiment, mountains 418 (or any other hill, or terrain,topological feature, foliage, or building(s) that might interfere withcell coverage areas) stand in between cell site device 402 and cell sitedevice 404. The mountains 418 can interfere with signals broadcast bycell site device 402, and as such, the system 400 can determine thatcell site device 402 will not be able to provide coverage for mobiledevices in the vicinity of cell site device 404. Accordingly, the modeloptimal solution has cell site device 406 providing coverage in cellcoverage area 416 for mobile devices in the vicinity of cell site device404. Without this determination performed by system 400, incrementaladjustments may never have found optimal configuration settings.

In an embodiment, system 400 can determine the location of cell sitedevices 402, 404, and 406 using GPS coordinates that are associated withthe cell site device station codes or other identifying information.Based on the GPS coordinates, the system can determine if there aretopological features, buildings, or other obstructions that may causeinterference with cell site device transmissions.

In another embodiment, system 400 can use mobile measurement reportsthat are received from mobile devices within range of cell site devices402, 404, and 406. The measurement reports can identify the signalstrength of the transmissions received from the cell site devices 402,404, and 406 at the mobile device. The system 400 can also receivelocations of the mobile devices (network location or by onboard GPScoordinates reported to the network) and the cell site devices.

Analyzing the signal strengths of the measurement reports with thelocations of the mobile devices and the cell site devices, the system400 can determine an RF propagation model for the area serviced by cellsite devices 402, 404, and 406 and identify areas of path loss,interference and obstruction based on the RF propagation model. Based onthe RF propagation model, the system 400 can calculate an optimalconfiguration setting for cell site devices 402 and 406.

The system 400 can update the simulated optimal configuration settingsat periodic, predetermined intervals or as needed in response todetecting a change to a condition affecting the optimal configurationsetting. In some embodiments, the system 400 can calculate severalsimulated optimal configuration settings that are based on differentenvironmental factors. For instance, RF propagation models can be timeof day dependent, season dependent (temperatures can affect path loss aswell as foliage in summer or lack of foliage in winter), or weatherdependent. The system 400 can determine different optimal configurationsettings for the different conditions, and depending on when the outageoccurs, select a configuration setting based on the RF propagation modelthat most closely resembles the outage conditions.

Turning now to FIG. 5, illustrated is an example, non-limitingembodiment of an efficient cell site outage mitigation system 500 inaccordance with various aspects described herein. FIG. 5 depicts anembodiment where system 500 determines model optimal configurationsettings for cell site devices that not only neighbor offline cellsites, but for cell site devices that neighbor the neighboring cell sitedevices.

For example, system 500 determines model configuration settings for cellsite devices 504, 506, 508, 510, 512, and 514 in response to a simulatedoutage at cell site device 502. Cell site devices 504, 506, and 508 canhave simulated configuration settings that allow their cell coverageareas to extend to the areas formerly covered by cell site device 502.In return cell site devices 504, 506, and 508 may lose areas which theywould have covered during normal operations. In response to that, cellsite devices 510, 512, and 514 can be provided with model configurationsettings that cover the areas formerly covered by cell site devices 504,506, and 508. The process can be repeated by as many cell site devicesas necessary as to mitigate the loss of coverage caused by an offlinecell site device.

Turning now to FIG. 6, illustrated is a block diagram of an example,non-limiting embodiment of an efficient cell site outage mitigationsystem 600 in accordance with various aspects described herein. A mobilenetwork 614 can include simulation component 616 that determines asimulated configuration setting for cell site devices 602, 604, and 606based on one of the cell site devices being offline.

In an embodiment, the simulation component 616 can determine simulatedconfiguration settings for cell site devices 602 and 606 in case cellsite device 604 goes offline. If cell site device 604 were to gooffline, mobile devices within cell coverage area 610 would loseconnectivity unless the mobile devices were in the areas of cellcoverage area 610 that overlap with cell coverage areas 608 and 612. Thesimulated configuration settings for cell site devices 602 and 606 canadjust the cell coverage areas 608 and 612 to cover as much of the areaof former cell coverage area 610 as possible.

In an embodiment, the simulated configuration settings for cell sitedevices 602 and 606 are stored and not put into use until an outage atcell site device 604 is detected. Simulated configuration settings foreach cell site device can be stored that are based on any of cell sitedevices 602, 604, and 606 going offline. When it is determined that acell site device has gone offline, adjustment component 618 adjusts theconfiguration settings using the simulated configuration settingsdetermined by simulation component 616. Adjustment component 618 selectsthe simulated configuration settings that corresponds to the cell sitedevice outage.

In an embodiment, simulation component 616 can determine simulatedconfiguration settings before an outage is detected. In otherembodiments, the simulation component 616 determines the simulatedconfiguration settings at the beginning of an outage. In someembodiments, simulation component 616 can determine a plurality ofsimulated configuration settings based on certain conditions (weather,time of day, season, temperature, etc). Adjustment component 618 canselect the simulated configuration setting by matching the conditions ofthe simulated configuration setting to the conditions at the time of theoutage.

In an embodiment, adjustment component 618 can continue adjusting theconfiguration setting after implementing the simulated configuration inresponse to a cell site outage. The simulated configuration setting canbe close to optimal, but continued iterative adjustments can improve thecoverage beyond the coverage provided by the simulated optimalconfiguration setting.

Turning now to FIG. 7, illustrated is a block diagram of an example,non-limiting embodiment of an efficient cell site outage mitigationsystem 700 in accordance with various aspects described herein. A mobilenetwork 712 can include simulation component 716 that determines asimulated configuration setting for cell site device 704 based on aneighboring cell site (not shown) being offline.

In an embodiment, simulation component 716 can determine the simulatedconfiguration setting based on RF propagation models, user distributionmodels, and user demand models determined by tracking component 714.Tracking component 714 can receive mobile measurement reports that arereceived from mobile devices 706 and 710 that are within cell coveragearea 702. The measurement reports can identify the signal strength ofthe transmissions received from the cell site device 704 at the mobiledevice 706 or 710. The tracking component 714 can also receive locationsof the mobile devices 706 and 710 (network location or by onboard GPScoordinates reported to the network) and the cell site device 704.

Analyzing the signal strengths of the measurement reports with thelocations of the mobile devices and the cell site devices, the trackingcomponent 714 can determine an RF propagation model for the areaserviced by cell site device 704 and identify areas of path loss,interference and obstruction based on the RF propagation model. Based onthe RF propagation model, the simulation component 716 can calculate anoptimal configuration setting for cell site device 704 in response to aneighboring cell site device going offline. Tracking component 714 cantake into account the current location of mobile devices within the areaas well as user demand. For instance, if the cell coverage area 702 hasa larger number of mobile devices than a neighboring area, during anoutage, the simulation component can give a higher priority to keepingcell coverage area 702 constant.

FIG. 8 illustrates a process in connection with the aforementionedsystems. The process in FIG. 8 can be implemented for example by systems100, 200, 300, 400, 500, 600, and 700 and illustrated in FIGS. 1-7respectively. While for purposes of simplicity of explanation, themethods are shown and described as a series of blocks, it is to beunderstood and appreciated that the claimed subject matter is notlimited by the order of the blocks, as some blocks may occur indifferent orders and/or concurrently with other blocks from what isdepicted and described herein. Moreover, not all illustrated blocks maybe required to implement the methods described hereinafter.

FIG. 8 illustrates a flow diagram of an example, non-limiting embodimentof a method for providing efficient cell site outage mitigation.Methodology 800 can begin at 802, where a model configuration settingfor a first base station device is determined, (e.g., by simulationcomponent 616) based on information relating to a disabled neighboringbase station device, wherein the model configuration setting provides acoverage model for an area associated with the first base station deviceand the disabled neighboring base station device.

If a base station device were to go offline, mobile devices within rangeof the base station device would lose connectivity unless the mobiledevices were in range of another base station device. The modelconfiguration setting for the first base station device adjusts the cellcoverage area of the first base station device to cover as much of thearea formerly covered by the neighboring base station device.

At 804, a configuration setting for the first base station device isadjusted (e.g., by adjustment component 618) to match the modelconfiguration setting in response to determining that the neighboringbase station device is offline. Once implemented, iterative correctionsto the real-time configuration settings can continue to be made toimprove the coverage area of the first base station device.

Referring now to FIG. 9, there is illustrated a block diagram of acomputing environment in accordance with various aspects describedherein. For example, in some embodiments, the computer can be or beincluded within the radio repeater system disclosed in any of theprevious systems 200, 300, 400, 500, 600 and/or 700.

In order to provide additional context for various embodiments describedherein, FIG. 9 and the following discussion are intended to provide abrief, general description of a suitable computing environment 900 inwhich the various embodiments of the embodiment described herein can beimplemented. While the embodiments have been described above in thegeneral context of computer-executable instructions that can run on oneor more computers, those skilled in the art will recognize that theembodiments can be also implemented in combination with other programmodules and/or as a combination of hardware and software.

Generally, program modules include routines, programs, components, datastructures, etc., that perform particular tasks or implement particularabstract data types. Moreover, those skilled in the art will appreciatethat the inventive methods can be practiced with other computer systemconfigurations, including single-processor or multiprocessor computersystems, minicomputers, mainframe computers, as well as personalcomputers, hand-held computing devices, microprocessor-based orprogrammable consumer electronics, and the like, each of which can beoperatively coupled to one or more associated devices.

The terms “first,” “second,” “third,” and so forth, as used in theclaims, unless otherwise clear by context, is for clarity only anddoesn't otherwise indicate or imply any order in time. For instance, “afirst determination,” “a second determination,” and “a thirddetermination,” does not indicate or imply that the first determinationis to be made before the second determination, or vice versa, etc.

The illustrated embodiments of the embodiments herein can be alsopracticed in distributed computing environments where certain tasks areperformed by remote processing devices that are linked through acommunications network. In a distributed computing environment, programmodules can be located in both local and remote memory storage devices.

Computing devices typically include a variety of media, which caninclude computer-readable storage media and/or communications media,which two terms are used herein differently from one another as follows.Computer-readable storage media can be any available storage media thatcan be accessed by the computer and includes both volatile andnonvolatile media, removable and non-removable media. By way of example,and not limitation, computer-readable storage media can be implementedin connection with any method or technology for storage of informationsuch as computer-readable instructions, program modules, structured dataor unstructured data.

Computer-readable storage media can include, but are not limited to,random access memory (RAM), read only memory (ROM), electricallyerasable programmable read only memory (EEPROM), flash memory or othermemory technology, compact disk read only memory (CD-ROM), digitalversatile disk (DVD) or other optical disk storage, magnetic cassettes,magnetic tape, magnetic disk storage or other magnetic storage devicesor other tangible and/or non-transitory media which can be used to storedesired information. In this regard, the terms “tangible” or“non-transitory” herein as applied to storage, memory orcomputer-readable media, are to be understood to exclude onlypropagating transitory signals per se as modifiers and do not relinquishrights to all standard storage, memory or computer-readable media thatare not only propagating transitory signals per se.

Computer-readable storage media can be accessed by one or more local orremote computing devices, e.g., via access requests, queries or otherdata retrieval protocols, for a variety of operations with respect tothe information stored by the medium.

Communications media typically embody computer-readable instructions,data structures, program modules or other structured or unstructureddata in a data signal such as a modulated data signal, e.g., a carrierwave or other transport mechanism, and includes any information deliveryor transport media. The term “modulated data signal” or signals refersto a signal that has one or more of its characteristics set or changedin such a manner as to encode information in one or more signals. By wayof example, and not limitation, communication media include wired media,such as a wired network or direct-wired connection, and wireless mediasuch as acoustic, RF, infrared and other wireless media.

With reference again to FIG. 9, the example environment 900 forimplementing various embodiments of the aspects described hereinincludes a computer 902, the computer 902 including a processing unit904, a system memory 906 and a system bus 908. The system bus 908couples system components including, but not limited to, the systemmemory 906 to the processing unit 904. The processing unit 904 can beany of various commercially available processors. Dual microprocessorsand other multi-processor architectures can also be employed as theprocessing unit 904.

The system bus 908 can be any of several types of bus structure that canfurther interconnect to a memory bus (with or without a memorycontroller), a peripheral bus, and a local bus using any of a variety ofcommercially available bus architectures. The system memory 906 includesROM 910 and RAM 912. A basic input/output system (BIOS) can be stored ina non-volatile memory such as ROM, erasable programmable read onlymemory (EPROM), EEPROM, which BIOS contains the basic routines that helpto transfer information between elements within the computer 902, suchas during startup. The RAM 912 can also include a high-speed RAM such asstatic RAM for caching data.

The computer 902 further includes an internal hard disk drive (HDD) 914(e.g., EIDE, SATA), which internal hard disk drive 914 can also beconfigured for external use in a suitable chassis (not shown), amagnetic floppy disk drive (FDD) 916, (e.g., to read from or write to aremovable diskette 918) and an optical disk drive 920, (e.g., reading aCD-ROM disk 922 or, to read from or write to other high capacity opticalmedia such as the DVD). The hard disk drive 914, magnetic disk drive 916and optical disk drive 920 can be connected to the system bus 908 by ahard disk drive interface 924, a magnetic disk drive interface 926 andan optical drive interface 928, respectively. The interface 924 forexternal drive implementations includes at least one or both ofUniversal Serial Bus (USB) and Institute of Electrical and ElectronicsEngineers (IEEE) 994 interface technologies. Other external driveconnection technologies are within contemplation of the embodimentsdescribed herein.

The drives and their associated computer-readable storage media providenonvolatile storage of data, data structures, computer-executableinstructions, and so forth. For the computer 902, the drives and storagemedia accommodate the storage of any data in a suitable digital format.Although the description of computer-readable storage media above refersto a hard disk drive (HDD), a removable magnetic diskette, and aremovable optical media such as a CD or DVD, it should be appreciated bythose skilled in the art that other types of storage media which arereadable by a computer, such as zip drives, magnetic cassettes, flashmemory cards, cartridges, and the like, can also be used in the exampleoperating environment, and further, that any such storage media cancontain computer-executable instructions for performing the methodsdescribed herein.

A number of program modules can be stored in the drives and RAM 912,including an operating system 930, one or more application programs 932,other program modules 934 and program data 936. All or portions of theoperating system, applications, modules, and/or data can also be cachedin the RAM 912. The systems and methods described herein can beimplemented utilizing various commercially available operating systemsor combinations of operating systems.

A user can enter commands and information into the computer 902 throughone or more wired/wireless input devices, e.g., a keyboard 938 and apointing device, such as a mouse 940. Other input devices (not shown)can include a microphone, an infrared (IR) remote control, a joystick, agame pad, a stylus pen, touch screen or the like. These and other inputdevices are often connected to the processing unit 904 through an inputdevice interface 942 that can be coupled to the system bus 908, but canbe connected by other interfaces, such as a parallel port, an IEEE 1394serial port, a game port, a universal serial bus (USB) port, an IRinterface, etc.

A monitor 944 or other type of display device can be also connected tothe system bus 908 via an interface, such as a video adapter 946. Inaddition to the monitor 944, a computer typically includes otherperipheral output devices (not shown), such as speakers, printers, etc.

The computer 902 can operate in a networked environment using logicalconnections via wired and/or wireless communications to one or moreremote computers, such as a remote computer(s) 948. The remotecomputer(s) 948 can be a workstation, a server computer, a router, apersonal computer, portable computer, microprocessor-based entertainmentappliance, a peer device or other common network node, and typicallyincludes many or all of the elements described relative to the computer902, although, for purposes of brevity, only a memory/storage device 950is illustrated. The logical connections depicted include wired/wirelessconnectivity to a local area network (LAN) 952 and/or larger networks,e.g., a wide area network (WAN) 954. Such LAN and WAN networkingenvironments are commonplace in offices and companies, and facilitateenterprise-wide computer networks, such as intranets, all of which canconnect to a global communications network, e.g., the Internet.

When used in a LAN networking environment, the computer 902 can beconnected to the local network 952 through a wired and/or wirelesscommunication network interface or adapter 956. The adapter 956 canfacilitate wired or wireless communication to the LAN 952, which canalso include a wireless AP disposed thereon for communicating with thewireless adapter 956.

When used in a WAN networking environment, the computer 902 can includea modem 958 or can be connected to a communications server on the WAN954 or has other means for establishing communications over the WAN 954,such as by way of the Internet. The modem 958, which can be internal orexternal and a wired or wireless device, can be connected to the systembus 908 via the input device interface 942. In a networked environment,program modules depicted relative to the computer 902 or portionsthereof, can be stored in the remote memory/storage device 950. It willbe appreciated that the network connections shown are example and othermeans of establishing a communications link between the computers can beused.

The computer 902 can be operable to communicate with any wirelessdevices or entities operatively disposed in wireless communication,e.g., a printer, scanner, desktop and/or portable computer, portabledata assistant, communications satellite, any piece of equipment orlocation associated with a wirelessly detectable tag (e.g., a kiosk,news stand, restroom), and telephone. This can include Wireless Fidelity(Wi-Fi) and BLUETOOTH® wireless technologies. Thus, the communicationcan be a predefined structure as with a conventional network or simplyan ad hoc communication between at least two devices.

Wi-Fi can allow connection to the Internet from a couch at home, a bedin a hotel room or a conference room at work, without wires. Wi-Fi is awireless technology similar to that used in a cell phone that enablessuch devices, e.g., computers, to send and receive data indoors and out;anywhere within the range of a base station. Wi-Fi networks use radiotechnologies called IEEE 802.11 (a, b, g, n, ac, etc.) to providesecure, reliable, fast wireless connectivity. A Wi-Fi network can beused to connect computers to each other, to the Internet, and to wirednetworks (which can use IEEE 802.3 or Ethernet). Wi-Fi networks operatein the unlicensed 2.4 and 5 GHz radio bands, at an 11 Mbps (802.11a) or54 Mbps (802.11b) data rate, for example or with products that containboth bands (dual band), so the networks can provide real-worldperformance similar to the basic 10BaseT wired Ethernet networks used inmany offices.

FIG. 10 presents an example embodiment 1000 of a mobile network platform1010 that can implement and exploit one or more aspects of the disclosedsubject matter described herein. Generally, wireless network platform1010 can include components, e.g., nodes, gateways, interfaces, servers,or disparate platforms, that facilitate both packet-switched (PS) (e.g.,internet protocol (IP), frame relay, asynchronous transfer mode (ATM))and circuit-switched (CS) traffic (e.g., voice and data), as well ascontrol generation for networked wireless telecommunication. As anon-limiting example, wireless network platform 1010 can be included intelecommunications carrier networks, and can be considered carrier-sidecomponents as discussed elsewhere herein. Mobile network platform 1010includes CS gateway node(s) 1012 which can interface CS traffic receivedfrom legacy networks like telephony network(s) 1040 (e.g., publicswitched telephone network (PSTN), or public land mobile network (PLMN))or a signaling system #7 (SS7) network 1070. Circuit switched gatewaynode(s) 1012 can authorize and authenticate traffic (e.g., voice)arising from such networks. Additionally, CS gateway node(s) 1012 canaccess mobility, or roaming, data generated through SS7 network 1070;for instance, mobility data stored in a visited location register (VLR),which can reside in memory 1030. Moreover, CS gateway node(s) 1012interfaces CS-based traffic and signaling and PS gateway node(s) 1018.As an example, in a 3GPP UMTS network, CS gateway node(s) 1012 can berealized at least in part in gateway GPRS support node(s) (GGSN). Itshould be appreciated that functionality and specific operation of CSgateway node(s) 1012, PS gateway node(s) 1018, and serving node(s) 1016,is provided and dictated by radio technology(ies) utilized by mobilenetwork platform 1010 for telecommunication.

In addition to receiving and processing CS-switched traffic andsignaling, PS gateway node(s) 1018 can authorize and authenticatePS-based data sessions with served mobile devices. Data sessions caninclude traffic, or content(s), exchanged with networks external to thewireless network platform 1010, like wide area network(s) (WANs) 1050,enterprise network(s) 1070, and service network(s) 1080, which can beembodied in local area network(s) (LANs), can also be interfaced withmobile network platform 1010 through PS gateway node(s) 1018. It is tobe noted that WANs 1050 and enterprise network(s) 1060 can embody, atleast in part, a service network(s) like IP multimedia subsystem (IMS).Based on radio technology layer(s) available in technology resource(s)1017, packet-switched gateway node(s) 1018 can generate packet dataprotocol contexts when a data session is established; other datastructures that facilitate routing of packetized data also can begenerated. To that end, in an aspect, PS gateway node(s) 1018 caninclude a tunnel interface (e.g., tunnel termination gateway (TTG) in3GPP UMTS network(s) (not shown)) which can facilitate packetizedcommunication with disparate wireless network(s), such as Wi-Finetworks.

In embodiment 1000, wireless network platform 1010 also includes servingnode(s) 1016 that, based upon available radio technology layer(s) withintechnology resource(s) 1017, convey the various packetized flows of datastreams received through PS gateway node(s) 1018. It is to be noted thatfor technology resource(s) 1017 that rely primarily on CS communication,server node(s) can deliver traffic without reliance on PS gatewaynode(s) 1018; for example, server node(s) can embody at least in part amobile switching center. As an example, in a 3GPP UMTS network, servingnode(s) 1016 can be embodied in serving GPRS support node(s) (SGSN).

For radio technologies that exploit packetized communication, server(s)1014 in wireless network platform 1010 can execute numerous applicationsthat can generate multiple disparate packetized data streams or flows,and manage (e.g., schedule, queue, format . . . ) such flows. Suchapplication(s) can include add-on features to standard services (forexample, provisioning, billing, customer support . . . ) provided bywireless network platform 1010. Data streams (e.g., content(s) that arepart of a voice call or data session) can be conveyed to PS gatewaynode(s) 1018 for authorization/authentication and initiation of a datasession, and to serving node(s) 1016 for communication thereafter. Inaddition to application server, server(s) 1014 can include utilityserver(s), a utility server can include a provisioning server, anoperations and maintenance server, a security server that can implementat least in part a certificate authority and firewalls as well as othersecurity mechanisms, and the like. In an aspect, security server(s)secure communication served through wireless network platform 1010 toensure network's operation and data integrity in addition toauthorization and authentication procedures that CS gateway node(s) 1012and PS gateway node(s) 1018 can enact. Moreover, provisioning server(s)can provision services from external network(s) like networks operatedby a disparate service provider; for instance, WAN 1050 or GlobalPositioning System (GPS) network(s) (not shown). Provisioning server(s)can also provision coverage through networks associated to wirelessnetwork platform 1010 (e.g., deployed and operated by the same serviceprovider), such as femto-cell network(s) (not shown) that enhancewireless service coverage within indoor confined spaces and offload RANresources in order to enhance subscriber service experience within ahome or business environment by way of UE 1075.

It is to be noted that server(s) 1014 can include one or more processorsconfigured to confer at least in part the functionality of macro networkplatform 1010. To that end, the one or more processor can execute codeinstructions stored in memory 1030, for example. It is should beappreciated that server(s) 1014 can include a content manager 1015,which operates in substantially the same manner as describedhereinbefore.

In example embodiment 1000, memory 1030 can store information related tooperation of wireless network platform 1010. Other operationalinformation can include provisioning information of mobile devicesserved through wireless platform network 1010, subscriber databases;application intelligence, pricing schemes, e.g., promotional rates,flat-rate programs, couponing campaigns; technical specification(s)consistent with telecommunication protocols for operation of disparateradio, or wireless, technology layers; and so forth. Memory 1030 canalso store information from at least one of telephony network(s) 1040,WAN 1050, enterprise network(s) 1060, or SS7 network 1070. In an aspect,memory 1030 can be, for example, accessed as part of a data storecomponent or as a remotely connected memory store.

In order to provide a context for the various aspects of the disclosedsubject matter, FIG. 10, and the following discussion, are intended toprovide a brief, general description of a suitable environment in whichthe various aspects of the disclosed subject matter can be implemented.While the subject matter has been described above in the general contextof computer-executable instructions of a computer program that runs on acomputer and/or computers, those skilled in the art will recognize thatthe disclosed subject matter also can be implemented in combination withother program modules. Generally, program modules include routines,programs, components, data structures, etc. that perform particulartasks and/or implement particular abstract data types.

In the subject specification, terms such as “store,” “storage,” “datastore,” data storage,” “database,” and substantially any otherinformation storage component relevant to operation and functionality ofa component, refer to “memory components,” or entities embodied in a“memory” or components comprising the memory. It will be appreciatedthat the memory components described herein can be either volatilememory or nonvolatile memory, or can include both volatile andnonvolatile memory, by way of illustration, and not limitation, volatilememory 1020 (see below), non-volatile memory 1022 (see below), diskstorage 1024 (see below), and memory storage 1046 (see below). Further,nonvolatile memory can be included in read only memory (ROM),programmable ROM (PROM), electrically programmable ROM (EPROM),electrically erasable ROM (EEPROM), or flash memory. Volatile memory caninclude random access memory (RAM), which acts as external cache memory.By way of illustration and not limitation, RAM is available in manyforms such as synchronous RAM (SRAM), dynamic RAM (DRAM), synchronousDRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM(ESDRAM), Synchlink DRAM (SLDRAM), and direct Rambus RAM (DRRAM).Additionally, the disclosed memory components of systems or methodsherein are intended to comprise, without being limited to comprising,these and any other suitable types of memory.

Moreover, it will be noted that the disclosed subject matter can bepracticed with other computer system configurations, includingsingle-processor or multiprocessor computer systems, mini-computingdevices, mainframe computers, as well as personal computers, hand-heldcomputing devices (e.g., PDA, phone, watch, tablet computers, netbookcomputers, . . . ), microprocessor-based or programmable consumer orindustrial electronics, and the like. The illustrated aspects can alsobe practiced in distributed computing environments where tasks areperformed by remote processing devices that are linked through acommunications network; however, some if not all aspects of the subjectdisclosure can be practiced on stand-alone computers. In a distributedcomputing environment, program modules can be located in both local andremote memory storage devices.

The embodiments described herein can employ artificial intelligence (AI)to facilitate automating one or more features described herein. Theembodiments (e.g., in connection with automatically identifying acquiredcell sites that provide a maximum value/benefit after addition to anexisting communication network) can employ various AI-based schemes forcarrying out various embodiments thereof. Moreover, the classifier canbe employed to determine a ranking or priority of the each cell site ofthe acquired network. A classifier is a function that maps an inputattribute vector, x=(x1, x2, x3, x4, . . . , xn), to a confidence thatthe input belongs to a class, that is, f(x)=confidence(class). Suchclassification can employ a probabilistic and/or statistical-basedanalysis (e.g., factoring into the analysis utilities and costs) toprognose or infer an action that a user desires to be automaticallyperformed. A support vector machine (SVM) is an example of a classifierthat can be employed. The SVM operates by finding a hypersurface in thespace of possible inputs, which the hypersurface attempts to split thetriggering criteria from the non-triggering events. Intuitively, thismakes the classification correct for testing data that is near, but notidentical to training data. Other directed and undirected modelclassification approaches include, e.g., naïve Bayes, Bayesian networks,decision trees, neural networks, fuzzy logic models, and probabilisticclassification models providing different patterns of independence canbe employed. Classification as used herein also is inclusive ofstatistical regression that is utilized to develop models of priority.

As will be readily appreciated, one or more of the embodiments canemploy classifiers that are explicitly trained (e.g., via a generictraining data) as well as implicitly trained (e.g., via observing UEbehavior, operator preferences, historical information, receivingextrinsic information). For example, SVMs can be configured via alearning or training phase within a classifier constructor and featureselection module. Thus, the classifier(s) can be used to automaticallylearn and perform a number of functions, including but not limited todetermining according to a predetermined criteria which of the acquiredcell sites will benefit a maximum number of subscribers and/or which ofthe acquired cell sites will add minimum value to the existingcommunication network coverage, etc.

As used in this application, in some embodiments, the terms “component,”“system” and the like are intended to refer to, or include, acomputer-related entity or an entity related to an operational apparatuswith one or more specific functionalities, wherein the entity can beeither hardware, a combination of hardware and software, software, orsoftware in execution. As an example, a component may be, but is notlimited to being, a process running on a processor, a processor, anobject, an executable, a thread of execution, computer-executableinstructions, a program, and/or a computer. By way of illustration andnot limitation, both an application running on a server and the servercan be a component. One or more components may reside within a processand/or thread of execution and a component may be localized on onecomputer and/or distributed between two or more computers. In addition,these components can execute from various computer readable media havingvarious data structures stored thereon. The components may communicatevia local and/or remote processes such as in accordance with a signalhaving one or more data packets (e.g., data from one componentinteracting with another component in a local system, distributedsystem, and/or across a network such as the Internet with other systemsvia the signal). As another example, a component can be an apparatuswith specific functionality provided by mechanical parts operated byelectric or electronic circuitry, which is operated by a software orfirmware application executed by a processor, wherein the processor canbe internal or external to the apparatus and executes at least a part ofthe software or firmware application. As yet another example, acomponent can be an apparatus that provides specific functionalitythrough electronic components without mechanical parts, the electroniccomponents can include a processor therein to execute software orfirmware that confers at least in part the functionality of theelectronic components. While various components have been illustrated asseparate components, it will be appreciated that multiple components canbe implemented as a single component, or a single component can beimplemented as multiple components, without departing from exampleembodiments.

Further, the various embodiments can be implemented as a method,apparatus or article of manufacture using standard programming and/orengineering techniques to produce software, firmware, hardware or anycombination thereof to control a computer to implement the disclosedsubject matter. The term “article of manufacture” as used herein isintended to encompass a computer program accessible from anycomputer-readable device or computer-readable storage/communicationsmedia. For example, computer readable storage media can include, but arenot limited to, magnetic storage devices (e.g., hard disk, floppy disk,magnetic strips), optical disks (e.g., compact disk (CD), digitalversatile disk (DVD)), smart cards, and flash memory devices (e.g.,card, stick, key drive). Of course, those skilled in the art willrecognize many modifications can be made to this configuration withoutdeparting from the scope or spirit of the various embodiments.

In addition, the words “example” and “exemplary” are used herein to meanserving as an instance or illustration. Any embodiment or designdescribed herein as “example” or “exemplary” is not necessarily to beconstrued as preferred or advantageous over other embodiments ordesigns. Rather, use of the word example or exemplary is intended topresent concepts in a concrete fashion. As used in this application, theterm “or” is intended to mean an inclusive “or” rather than an exclusive“or”. That is, unless specified otherwise or clear from context, “Xemploys A or B” is intended to mean any of the natural inclusivepermutations. That is, if X employs A; X employs B; or X employs both Aand B, then “X employs A or B” is satisfied under any of the foregoinginstances. In addition, the articles “a” and “an” as used in thisapplication and the appended claims should generally be construed tomean “one or more” unless specified otherwise or clear from context tobe directed to a singular form.

Moreover, terms such as “user equipment,” “mobile station,” “mobile,”subscriber station,” “access terminal,” “terminal,” “handset,” “mobiledevice” (and/or terms representing similar terminology) can refer to awireless device utilized by a subscriber or user of a wirelesscommunication service to receive or convey data, control, voice, video,sound, gaming or substantially any data-stream or signaling-stream. Theforegoing terms are utilized interchangeably herein and with referenceto the related drawings.

Furthermore, the terms “user,” “subscriber,” “customer,” “consumer” andthe like are employed interchangeably throughout, unless contextwarrants particular distinctions among the terms. It should beappreciated that such terms can refer to human entities or automatedcomponents supported through artificial intelligence (e.g., a capacityto make inference based, at least, on complex mathematical formalisms),which can provide simulated vision, sound recognition and so forth.

As employed herein, the term “processor” can refer to substantially anycomputing processing unit or device comprising, but not limited tocomprising, single-core processors; single-processors with softwaremultithread execution capability; multi-core processors; multi-coreprocessors with software multithread execution capability; multi-coreprocessors with hardware multithread technology; parallel platforms; andparallel platforms with distributed shared memory. Additionally, aprocessor can refer to an integrated circuit, an application specificintegrated circuit (ASIC), a digital signal processor (DSP), a fieldprogrammable gate array (FPGA), a programmable logic controller (PLC), acomplex programmable logic device (CPLD), a discrete gate or transistorlogic, discrete hardware components or any combination thereof designedto perform the functions described herein. Processors can exploitnano-scale architectures such as, but not limited to, molecular andquantum-dot based transistors, switches and gates, in order to optimizespace usage or enhance performance of user equipment. A processor canalso be implemented as a combination of computing processing units.

As used herein, terms such as “data storage,” data storage,” “database,”and substantially any other information storage component relevant tooperation and functionality of a component, refer to “memorycomponents,” or entities embodied in a “memory” or components comprisingthe memory. It will be appreciated that the memory components orcomputer-readable storage media, described herein can be either volatilememory or nonvolatile memory or can include both volatile andnonvolatile memory.

Memory disclosed herein can include volatile memory or nonvolatilememory or can include both volatile and nonvolatile memory. By way ofillustration, and not limitation, nonvolatile memory can include readonly memory (ROM), programmable ROM (PROM), electrically programmableROM (EPROM), electrically erasable PROM (EEPROM) or flash memory.Volatile memory can include random access memory (RAM), which acts asexternal cache memory. By way of illustration and not limitation, RAM isavailable in many forms such as static RAM (SRAM), dynamic RAM (DRAM),synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhancedSDRAM (ESDRAM), Synchlink DRAM (SLDRAM), and direct Rambus RAM (DRRAM).The memory (e.g., data storages, databases) of the embodiments areintended to comprise, without being limited to, these and any othersuitable types of memory.

What has been described above includes mere examples of variousembodiments. It is, of course, not possible to describe everyconceivable combination of components or methodologies for purposes ofdescribing these examples, but one of ordinary skill in the art canrecognize that many further combinations and permutations of the presentembodiments are possible. Accordingly, the embodiments disclosed and/orclaimed herein are intended to embrace all such alterations,modifications and variations that fall within the spirit and scope ofthe appended claims. Furthermore, to the extent that the term “includes”is used in either the detailed description or the claims, such term isintended to be inclusive in a manner similar to the term “comprising” as“comprising” is interpreted when employed as a transitional word in aclaim.

What is claimed is:
 1. A system, comprising: a memory to storeexecutable instructions; and a processor, coupled to the memory, tofacilitate execution of the executable instructions to performoperations, comprising: determining a first simulated configurationsetting for a first cell site device based on a simulated disablement ofa second cell site device, wherein the first simulated configurationsetting enables a simulated coverage model for an area associated withthe first cell site device and the second cell site device, andadjusting a configuration setting for the first cell site device tomatch the first simulated configuration setting in response todetermining that the second cell site device is disabled, wherein theconfiguration setting comprises a transmission power setting and a tiltangle setting for an antenna associated with the first cell site device;receiving feedback relating to coverage of the area; and updating theconfiguration setting in response to the feedback according to afunction that increases coverage of the area.
 2. The system of claim 1,wherein the operations further comprise: repeating the updating theconfiguration setting until the coverage of the area satisfies apredetermined coverage level.
 3. The system of claim 2, wherein theoperations further comprise: checking for the change to the conditionaffecting the simulated coverage model at a set time.
 4. The system ofclaim 1, wherein the operations further comprise: determining that achange to a condition affecting the simulated coverage model hasoccurred; and updating the first simulated configuration setting basedon the change.
 5. The system of claim 1, wherein the operations furthercomprise: determining the first simulated configuration setting before aplanned outage.
 6. The system of claim 1, wherein the first simulatedconfiguration setting is based on a location of a mobile device in thearea associated with the first cell site device and the second cell sitedevice.
 7. The system of claim 1, wherein the first simulatedconfiguration setting is based on a network usage of a mobile device inthe area associated with the first cell site device and the second cellsite device.
 8. The system of claim 7, wherein the first simulatedconfiguration setting is further based on a measurement report receivedfrom a mobile device.
 9. The system of claim 1, wherein the firstsimulated configuration setting is based on an environmental factor, aterrain factor, and a distribution of cell site devices.
 10. The systemof claim 1, wherein the operations further comprise: determining asecond simulation configuration setting for a third cell site devicethat neighbors the first cell site device based on the first simulatedconfiguration setting and the simulated coverage model for the area. 11.A method, comprising: determining, by a device comprising a processor, amodel configuration setting for a first base station device based oninformation relating to a disabled neighboring base station device,wherein the model configuration setting provides a coverage model for anarea associated with the first base station device and the disabledneighboring base station device; and modifying a configuration settingcomprising an antenna power level and an antenna tilt angle of anantenna associated with the first base station device for the first basestation device to match the model configuration setting in response todetermining that the neighboring base station device is offline.
 12. Themethod of claim 11, further comprising: incrementally adjusting theconfiguration setting to increase coverage for the area.
 13. The methodof claim 11, further comprising: updating the model configurationsetting in response to detecting a change in a condition affecting thecoverage model.
 14. The method of claim 11, wherein the determining themodel configuration setting is performed before the neighboring basestation device is determined to have gone offline.
 15. The method ofclaim 11, wherein the determining the model configuration setting isbased on data representing a radio frequency (RF) propagation model, auser demand model and a user distribution model.
 16. The method of claim15, wherein the determining the RF propagation model is based on datarepresenting an environmental factor, a terrain factor, and a basestation device distribution model.
 17. A non-transitory machine-readablestorage medium, comprising executable instructions that, when executedby a processor, facilitate performance of operations, comprising:modeling a simulated configuration setting for a first base stationdevice based on an offline second base station device that neighbors thefirst base station device, wherein the simulated configuration settingenables a coverage model for an area associated with the first basestation device and the offline second base station device; adjusting aconfiguration setting for the first base station device to match thesimulated configuration setting in response to determining that thesecond base station device is offline; receiving feedback relating tocoverage of the area; and updating the configuration setting in responseto the feedback according to a function that increases coverage of thearea.
 18. The non-transitory machine-readable storage medium of claim17, wherein the operations further comprise: incrementally adjusting theconfiguration setting to improve coverage for the area.
 19. Thenon-transitory machine-readable storage medium of claim 18, wherein theoperations further comprise: modeling another simulated coverage settingfor another base station device that neighbors the first base stationdevice and is in another area distinct from the area, and wherein theother simulated coverage setting is based on the simulated configurationsetting and the coverage model for the area.
 20. The non-transitorymachine-readable storage medium of claim 18, wherein the operationsfurther comprise: updating the simulated configuration setting inresponse to detecting a change in a condition affecting the coveragemodel.